@techreport{elediasc12733,
            year = {2016},
       publisher = {University of Trento},
            type = {Technical Report},
           title = {An Innovative Particle Swarm Optimization?Based Approach for GPR Microwave Imaging},
          author = {M. Salucci and L. Poli and N. Anselmi and A. Massa},
        abstract = {This work presents an innovative microwave imaging technique for accurate and robust subsurface imaging. The proposed approach is based on the integration of a customized particle swarm optimization (PSO) algorithm within the iterative multi-scaling approach (IMSA), and exploits multiple frequency components extracted from ground penetrating radar (GPR) wideband data. The solution of the arising inverse scattering problem is yielded within a multi-frequency (MF) approach, allowing to exploit the intrinsic frequency diversity of GPR measurements in order to add information and mitigate the ill-posedness and non-linearity issues. Some numerical experiments are shown in order to assess the effectiveness of the proposed MF-IMSA-PSO method when dealing with the retrieval of unknown buried scatterers having different shape. Moreover, a comparison to a competitive state-of-the-art deterministic approach is shown, in order to highlight the benefits of exploiting a global optimization algorithm in minimizing the MF cost function.},
        keywords = {Ground Penetrating Radar (GPR), Inverse Scattering (IS), Multi-Frequency (MF), Particle Swarm Optimization (PSO), Stochastic Optimization, Wide-band Data, Iterative Multi Scaling Approach (IMSA)  },
             url = {http://www.eledia.org/students-reports/733/}
}